Azimuth calibration method and device for spaceborne radar image, equipment and storage medium

Abstract

The invention provides an azimuth calibration method and device for a spaceborne radar image, equipment and a storage medium. The method comprises the following steps: determining each-order phase coefficient of an azimuth signal corresponding to a scattering point in a spaceborne radar image; for each scattering point, determining a rotation motion parameter of the scattering point according to the phase coefficient of each order and a first mapping relation; the rotation motion parameters comprise an initial rotation speed and a rotation acceleration; the first mapping relation is used for representing a mapping relation between each order of phase coefficient and the rotation motion parameter; determining the azimuth resolution of the spaceborne radar image according to the rotational motion parameter of at least one scattering point; and calibrating the azimuth of the spaceborne radar image according to the azimuth resolution to obtain the calibrated spaceborne radar image.

Description

TECHNICAL FIELD

[0001] The present application relates to remote sensing image processing technology, and relates to, but is not limited to, a method and device for azimuth calibration of a spaceborne radar image, equipment and a storage medium. BACKGROUND

[0002] Spaceborne radar imaging technology is an important means of space target detection and identification, and a two-dimensional image of a target is reconstructed through a radar echo signal to support analysis of the size, shape and motion state of the target. In actual applications, the relative motion relationship between the radar and the target is complex, which affects the accurate reconstruction of the size and shape of the target in the image. Therefore, it is urgent to develop an accurate transverse (i.e., azimuth) calibration technology to accurately calibrate the azimuth size of a spaceborne radar image of a space target, to enhance the interpretation capability of the image for the space target, and to promote the practical value of spaceborne radar imaging technology. SUMMARY

[0003] Embodiments of the present application provide a method and device for azimuth calibration of a spaceborne radar image, equipment and a storage medium; wherein

[0004] In a first aspect, the embodiments of the present application provide a method for azimuth calibration of a spaceborne radar image, the method comprising: determining phase coefficients of each order of an azimuth signal corresponding to a scattering point in the spaceborne radar image; for each scattering point, determining a rotational motion parameter of the scattering point according to the phase coefficients of each order and a first mapping relationship; the rotational motion parameter comprises a rotational initial velocity and a rotational acceleration; the first mapping relationship is used to represent a mapping relationship between the phase coefficients of each order and the rotational motion parameter; determining an azimuth resolution size of the spaceborne radar image according to the rotational motion parameter of at least one scattering point; and calibrating an azimuth direction of the spaceborne radar image according to the azimuth resolution size, to obtain a calibrated spaceborne radar image.

[0005] In a second aspect, the embodiments of the present application provide a device for azimuth calibration of a spaceborne radar image, the device comprising: a first determining module configured to determine phase coefficients of each order of an azimuth signal corresponding to a scattering point in the spaceborne radar image; a second determining module configured to, for each scattering point, determine a rotational motion parameter of the scattering point according to the phase coefficients of each order and a first mapping relationship; the rotational motion parameter comprises a rotational initial velocity and a rotational acceleration; the first mapping relationship is used to represent a mapping relationship between the phase coefficients of each order and the rotational motion parameter; a third determining module configured to determine an azimuth resolution size of the spaceborne radar image according to the rotational motion parameter of at least one scattering point; and a calibration module configured to calibrate an azimuth direction of the spaceborne radar image according to the azimuth resolution size, to obtain a calibrated spaceborne radar image.

[0006] In a third aspect, an electronic device is provided, which includes a memory and a processor, the memory storing a computer program capable of running on the processor, and the processor implements the method of the first aspect when executing the program.

[0007] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program, and the computer program, when executed by a processor, implements the method of the first aspect.

[0008] In a fifth aspect, a computer program product is provided, which includes a computer program or instructions, and the computer program or instructions, when executed by a processor, implements the method of the first aspect.

[0009] In a sixth aspect, a computer program is provided, which causes a processor to execute the method of the first aspect.

[0010] In the embodiments of the present application, the rotation initial velocity and the rotation acceleration in the rotation motion parameters are determined through the phase coefficients of each order of the azimuth signals corresponding to the scattering points in the spaceborne radar image and the mapping relationship between the phase coefficients of each order and the rotation motion parameters respectively. In this way, the resolution size of the spaceborne radar image in the azimuth direction is obtained according to the determined rotation initial velocity and rotation acceleration. Then, the azimuth direction of the spaceborne radar image is calibrated according to the azimuth resolution size, and the calibrated spaceborne radar image is obtained. In this way, the direct estimation of the rotation motion parameters is realized, the error accumulation caused by the iterative estimation is avoided, the calculation complexity is reduced, the azimuth calibration accuracy and stability of the spaceborne radar image are improved, and the method is especially suitable for high dynamic spaceborne radar imaging scenarios.

[0011] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and are not limiting to the present application. BRIEF DESCRIPTION OF DRAWINGS

[0012] The accompanying drawings, which are incorporated into and form a part of the specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the application. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0013] The flowchart shown in the accompanying drawings is only an exemplary illustration, and is not necessarily required to include all contents and operations / steps, nor is it necessarily required to be executed in the order described. For example, some operations / steps can be further divided, and some operations / steps can be combined or partially combined, so that the actual execution order may be changed according to the actual situation.

[0014] Figure 1 An implementation flowchart of a method for azimuth calibration of a spaceborne radar image according to an embodiment of the present application is shown in FIG. 1.

[0015] Figure 2 An implementation flowchart of a method for determining azimuth resolution according to an embodiment of the present application is shown in FIG. 2.

[0016] Figure 3 A space target scattering point model according to an embodiment of the present application is shown in FIG. 3.

[0017] Figure 4 A space target spaceborne radar image without azimuth calibration according to an embodiment of the present application is shown in FIG. 4.

[0018] Figure 5 A calibrated space target spaceborne radar image according to an embodiment of the present application is shown in FIG. 5.

[0019] Figure 6 A structure diagram of an azimuth calibration device for a spaceborne radar image according to an embodiment of the present application is shown in FIG. 6.

[0020] Figure 7 A structure diagram of an electronic device according to an embodiment of the present application is shown in FIG. 7. DETAILED DESCRIPTION

[0021] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the following will further describe the specific technical solutions of the present application with reference to the drawings in the embodiments of the present application. The following embodiments are used to describe the present application, but are not used to limit the scope of the present application.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description herein is for describing the embodiments of the present application only and is not intended to limit the present application.

[0023] In the following description, "some embodiments", "this embodiment", "embodiments of the present application" and the like describe a subset of all possible embodiments, but it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0024] The "first", "second", "third" and the like appearing in the embodiments of the present application do not have a specific meaning (such as no order, nor represent a special limitation on the number of devices in the embodiments of the present application), but only for the convenience of clearly describing the embodiments of the present application, and cannot constitute any limitation on the embodiments of the present application.

[0025] To facilitate understanding of the technical solutions of the embodiments of this application, the relevant technologies or terms of the embodiments of this application are described below. The following relevant technologies or terms are optional solutions and can be combined with the technical solutions of the embodiments of this application in any way, and all of them fall within the protection scope of the embodiments of this application.

[0026] In related technologies, lateral (i.e., orientation) calibration techniques include: lateral calibration methods based on image registration or image cross-correlation, lateral calibration methods based on optimal image quality, and lateral calibration methods based on projection vectors.

[0027] The inventors of this application, through research and analysis, discovered that lateral calibration methods based on image registration or image cross-correlation, as well as lateral calibration methods based on optimal image quality, require iterative estimation of rotational motion parameters through multiple radar imaging processes to achieve azimuth and scale calibration of radar images, facing high computational burden and local convergence risks. Lateral calibration methods based on projection vectors are typically combined with factorization and 3D reconstruction techniques, resulting in complex implementation processes, reliance on multi-stage parameter estimation, and a tendency to accumulate estimation errors, thus affecting the accuracy and stability of lateral calibration.

[0028] In view of the analysis of the principles underlying the aforementioned technical problems, embodiments of this application provide an image processing method. Figure 1 This is a schematic diagram illustrating the implementation process of the azimuth calibration method for spaceborne radar images provided in an embodiment of this application. Figure 1 As shown, the method includes the following steps 101 to 104:

[0029] Step 101: Determine the phase coefficients of each order of the azimuth signal corresponding to the scattering point in the spaceborne radar image;

[0030] Step 102: For each scattering point, determine the rotational motion parameters of the scattering point according to the phase coefficients of each order and the first mapping relationship; the rotational motion parameters include: initial rotational velocity and rotational acceleration; the first mapping relationship is used to characterize the mapping relationship between the phase coefficients of each order and the rotational motion parameters respectively;

[0031] Step 103: Determine the azimuth resolution of the spaceborne radar image based on the rotational motion parameters of at least one scattering point;

[0032] Step 104: Based on the azimuth resolution, calibrate the azimuth direction of the spaceborne radar image to obtain the calibrated spaceborne radar image.

[0033] It is understood that, in this embodiment, the initial rotational velocity and rotational acceleration in the rotational motion parameters are determined by using the phase coefficients of the azimuth signals corresponding to the scattering points in the spaceborne radar image and the mapping relationship between the phase coefficients and the rotational motion parameters. Thus, based on the determined initial rotational velocity and rotational acceleration, the azimuth resolution of the spaceborne radar image is obtained. Therefore, based on the azimuth resolution, the azimuth direction of the spaceborne radar image is calibrated to obtain the calibrated spaceborne radar image. This achieves direct estimation of the rotational motion parameters, avoids error accumulation caused by iterative estimation, reduces computational complexity, and improves the azimuth calibration accuracy and stability of the spaceborne radar image, making it particularly suitable for high-dynamic spaceborne radar imaging scenarios.

[0034] The following sections will describe further optional implementation methods for each of the above steps, as well as related terms.

[0035] In step 101, the phase coefficients of each order of the azimuth signal corresponding to the scattering point in the spaceborne radar image are determined.

[0036] It should be understood that the spaceborne radar image is not limited in the embodiments of this application. The spaceborne radar image refers to target imaging data acquired by a Synthetic Aperture Radar (SAR) or Inverse Synthetic Aperture Radar (ISAR) system mounted on a satellite, which contains two-dimensional information of the target in the range and azimuth directions, and is used for the state perception and identification of space targets.

[0037] In this embodiment, the term "scattering point" is not limited. The scattering point refers to a local area with significant reflective characteristics in a spaceborne radar image, typically corresponding to a specific part of the target structure, such as a metal component or structural edge. The echo signal from the scattering point can be used to extract the target's motion characteristics.

[0038] It should be understood that the azimuth signal is not limited in the embodiments of this application. The azimuth signal is closely related to the direction of motion of the radar platform. When an aircraft or satellite flies along a flight path, it transmits pulse signals toward the target point and receives signals reflected by the target. By processing these signals, a virtual large-aperture radar system can be synthesized, thereby obtaining a high-resolution image in the azimuth direction.

[0039] In this embodiment, the phase coefficient is not limited. The phase coefficient refers to the frequency domain manifestation of the Doppler effect caused by target motion during radar signal propagation, specifically expressed as a polynomial expansion of the phase of the azimuth signal over time. In some embodiments, the phase coefficients include: first-order phase coefficient, second-order phase coefficient, and third-order phase coefficient.

[0040] It should be understood that, in the embodiments of this application, the specific implementation method for determining the phase coefficients of each order of the azimuth signal corresponding to the scattering point in the spaceborne radar image is not limited. In some embodiments, determining the phase coefficients of each order of the azimuth signal corresponding to the scattering point in the spaceborne radar image includes: determining the phase coefficients of each order of the azimuth signal corresponding to the m-th scattering point in the spaceborne radar image; clearing the m-th scattering point in the spaceborne radar image, and performing the next step of determining the phase coefficients of each order of the azimuth signal corresponding to the scattering point in the spaceborne radar image, until the energy of the azimuth signal corresponding to the remaining scattering point is less than or equal to an energy threshold.

[0041] It is understood that in the embodiments of this application, the phase coefficients of each order of multiple scattering points are determined, and then the rotational motion parameters corresponding to the phase coefficients of each order of multiple scattering points are determined respectively. This is beneficial for calibrating the azimuth of the spaceborne radar image based on the rotational motion parameters of multiple scattering points, thereby reducing the error of the determined rotational motion parameters and further improving the azimuth calibration accuracy and stability of the spaceborne radar image.

[0042] It should be understood that, in the embodiments of this application, the m-th scattering point in the spaceborne radar image is not limited. The m-th scattering point in the spaceborne radar image can be any scattering point in the spaceborne radar image. In some embodiments, the m-th scattering point in the spaceborne radar image is the scattering point with the highest energy at a certain range cell in the spaceborne radar image.

[0043] In this embodiment, the energy threshold is not limited; it can be preset or determined based on the target in the spaceborne radar image. In some embodiments, the energy threshold is 0.1 times the energy of the original azimuth signal.

[0044] It should be understood that, in the embodiments of this application, the specific implementation method for determining the phase coefficients of each order of the azimuth signal corresponding to the scattering point in the spaceborne radar image is not limited. In some embodiments, determining the phase coefficients of each order of the azimuth signal corresponding to the scattering point in the spaceborne radar image includes: determining the third-order phase coefficient of the azimuth signal corresponding to the scattering point in the spaceborne radar image based on the product of the generalized cubic phase function; determining the second-order phase coefficient of the azimuth signal corresponding to the scattering point in the spaceborne radar image based on the integral of the cubic phase function; and determining the first-order phase coefficient of the azimuth signal corresponding to the scattering point in the spaceborne radar image based on the delinear frequency modulation algorithm.

[0045] For example, in one possible implementation, the phase coefficients of the scattering points can be obtained through phase parameter estimation methods. For instance, the third-order phase coefficients of the azimuth signal can be estimated using the Product Generalized Cubic Phase Function (PGCPF). The PGCPF achieves signal energy aggregation through delay, correlation, and Fourier transform, thereby accurately estimating the third-order phase coefficients and offering advantages such as suppressing cross-terms and improving noise immunity.

[0046] Based on the estimated third-order phase coefficients, the cubic phase is demodulated, and the remaining azimuth signal can be considered as a linear frequency modulated signal. Then, the second-order phase coefficients of the azimuth signal are estimated using the integrated cubic phase function (ICPF). The kernel function of the ICPF can concentrate the signal energy at the second-order phase coefficients, thereby achieving accurate estimation of the second-order phase coefficients and effectively suppressing cross-terms, making it suitable for low signal-to-noise ratio scenarios.

[0047] Based on the estimated second-order phase coefficients, the second-order phase is demodulated, and the remaining azimuth signal can be regarded as a single-frequency signal. Then, the first-order phase coefficients of the azimuth signal are estimated using the delinear frequency modulation (Decirp) method, which has the advantages of low computational complexity and simple implementation.

[0048] For cases where there are multiple scattering points on a single range cell, the CLEAN technique is used to eliminate scattering points with estimated phase coefficients of each order.

[0049] In step 102, for each scattering point, the rotational motion parameters of the scattering point are determined according to the phase coefficients of each order and the first mapping relationship; the rotational motion parameters include: initial rotational velocity and rotational acceleration; the first mapping relationship is used to characterize the mapping relationship between the phase coefficients of each order and the rotational motion parameters respectively.

[0050] It is understood that, in this embodiment of the application, the step of determining the rotational motion parameters of the scattering point based on the phase coefficients of each order and the first mapping relationship achieves direct analytical estimation of the target rotation state by constructing a high-precision mapping model between the phase parameters and the motion parameters. Thus, it does not rely on image quality optimization or multi-stage parameter estimation, resulting in low computational complexity and strong stability, making it suitable for spaceborne radar imaging tasks in highly dynamic scenarios.

[0051] It should be understood that in the embodiments of this application, the initial rotation velocity refers to the initial angular velocity when rotation begins around a certain axis, while the rotation acceleration refers to the rate of change of the initial rotation velocity over time. These two parameters, initial rotation velocity and rotation acceleration, together determine the equivalent rotation state of the target and are key input variables for achieving azimuth calibration.

[0052] In this embodiment, the first mapping relationship is not limited. In some embodiments, in the first mapping relationship, the relationship between each order phase coefficient and the initial rotational velocity and rotational acceleration is an Nth-order nonlinear relationship; N is the order corresponding to each order phase coefficient.

[0053] It should be understood that in some embodiments, the relationship between each phase coefficient and the initial rotational velocity and rotational acceleration is an Nth-order nonlinear relationship, including: the relationship between the first-order phase coefficient and the initial rotational velocity and rotational acceleration is a first-order nonlinear relationship; the relationship between the second-order phase coefficient and the initial rotational velocity and rotational acceleration is a second-order nonlinear relationship; and the relationship between the third-order phase coefficient and the initial rotational velocity and rotational acceleration is a third-order nonlinear relationship.

[0054] It is understood that in the embodiments of this application, the relationship between each order phase coefficient and the initial rotational velocity and rotational acceleration is an Nth-order nonlinear relationship, where N is the order corresponding to each order phase coefficient. Therefore, it is difficult to solve the rotational motion parameters based on the first mapping relationship between each order phase coefficient and the phase coefficient, and the solved rotational motion parameters may not conform to the physical meaning.

[0055] Further, in some embodiments, determining the rotational motion parameters of the scattering point based on the phase coefficients of each order and the first mapping relationship includes: determining the rotational motion parameters of the scattering point based on the phase coefficients of each order and the first mapping relationship when the relationship between the first-order phase coefficient and the third-order phase coefficient satisfies a first condition; the first condition includes: the first-order phase coefficient is greater than 0 and the third-order phase coefficient is less than 0; or, the first-order phase coefficient is less than 0 and the third-order phase coefficient is greater than 0; or, the product between the first-order phase coefficient and the third-order phase coefficient is less than 0.

[0056] It is understood that, in the embodiments of this application, the inventors discovered that when the signs of the first-order phase coefficient and the third-order phase coefficient are opposite, the initial rotational velocity and rotational acceleration obtained by solving according to the first mapping relationship between each order phase coefficient and the first phase coefficient include unique real solutions. Thus, under the condition of satisfying the first condition, determining the rotational motion parameters of the scattering point helps ensure that the solved rotational motion parameters have uniqueness and physical meaning, further improving the stability and accuracy of the calibration results.

[0057] It should be understood that, in the embodiments of this application, the first condition is used to screen scattering points whose phase coefficients satisfy a specific relationship, so as to ensure the uniqueness of subsequent rotational motion parameter estimation.

[0058] In this embodiment, since the relationship between each phase coefficient and the initial rotational velocity and rotational acceleration is an Nth-order nonlinear relationship, it can more accurately reflect the effect of the rotational characteristics of the real target on the azimuth signal phase. For targets in highly dynamic scenarios, such as high-speed rotating targets or targets with frequent attitude changes, it has higher estimation accuracy and stronger adaptability compared to linear models. This further improves the stability and reliability of rotational motion parameters, thereby achieving high-precision azimuth calibration of spaceborne radar images.

[0059] In some embodiments, determining the rotational motion parameters of the scattering point based on the phase coefficients of each order and the first mapping relationship includes: obtaining candidate rotational motion parameters of the scattering point based on the phase coefficients of each order and the first mapping relationship; determining the candidate rotational motion parameters that satisfy a second condition as the rotational motion parameters of the scattering point; the second condition is that the numerical value corresponding to the candidate rotational motion parameter is a real number.

[0060] It is understood that, in this embodiment of the application, if the relationship between the first-order phase coefficient and the third-order phase coefficient satisfies a first condition, it indicates that the initial rotational velocity and rotational acceleration obtained from the first mapping relationship between each order phase coefficient include unique real-valued solutions. Therefore, from the candidate rotational motion parameters of the scattering point obtained from the first mapping relationship between each order phase coefficient, rotational motion parameters whose corresponding values ​​are real-valued are determined. This helps to ensure that the determined rotational motion parameters have physical meaning.

[0061] It should be understood that, in the embodiments of this application, the candidate rotational motion parameters refer to the rotational motion parameters solved according to the phase coefficients of each order and the first mapping relationship, and the rotational motion parameters refer to the rotational motion parameters that satisfy the physical meaning, that is, the rotational motion parameters that can participate in the azimuth calibration solution.

[0062] In this embodiment, the second condition is used to filter out rotational motion parameters whose numerical type is real from all candidate rotational motion parameters. This is because, on the one hand, the processing environment of spaceborne radar images is complex and subject to significant noise interference, and some candidate rotational motion parameters may have complex solutions or unreasonable imaginary components. On the other hand, since the relationship between each order phase coefficient and the initial rotational velocity and rotational acceleration is an Nth-order nonlinear relationship, i.e., there is a high degree of coupling between each order phase coefficient and the initial rotational velocity and rotational acceleration, the rotational motion parameters solved based on the phase coefficients and the first mapping relationship may have complex solutions. In this case, directly using candidate rotational motion parameters for calibration will lead to unstable or even erroneous results. This is because the true rotational motion parameters should be real numbers, not complex numbers; otherwise, the solved rotational motion parameters have no actual physical meaning. Therefore, setting the numerical type as real numbers as the screening criterion can effectively eliminate invalid solutions and improve the accuracy and reliability of the determined rotational motion parameters.

[0063] In some embodiments, the first mapping relationship is obtained based on the second mapping relationship and the third mapping relationship; wherein, the second mapping relationship is used to characterize the mapping relationship between the azimuth signal corresponding to the scattering point in the spaceborne radar image and the rotational motion parameter; the third mapping relationship is used to characterize the mapping relationship between the azimuth signal corresponding to the scattering point and the phase coefficients of each order of the azimuth signal.

[0064] It is understood that, in this embodiment, a first mapping relationship is determined to characterize the azimuth signal corresponding to a scattering point in a spaceborne radar image and its rotational motion parameters through a second mapping relationship characterizing the azimuth signal and its phase coefficients of each order. This establishes a correlation between the phase coefficients of each order and the rotational motion parameters based on the azimuth signal. This facilitates the direct calculation of the rotational motion parameters of the scattering point based on the phase coefficients of each order and the first mapping relationship. Thus, high-precision azimuth calibration of spaceborne radar images can be achieved without relying on image quality optimization or multi-stage parameter estimation.

[0065] It should be understood that, in the embodiments of this application, the second mapping relationship is not limited, and the second mapping relationship is used to describe how the azimuth signal is affected by rotational motion. In some embodiments, the second mapping relationship is obtained based on the fourth mapping relationship and the fifth mapping relationship; the fourth mapping relationship is used to characterize the mapping relationship between the slant range history of the scattering point and the rotation angle, the rotation angle being determined based on the initial rotational velocity and rotational acceleration; the fifth mapping relationship is used to characterize the mapping relationship between the azimuth signal of the scattering point and the slant range history of the scattering point.

[0066] In this embodiment, the nonlinear coupling relationship between the phase coefficients of the azimuth signal and the rotational motion parameters is obtained through the second and third mapping relationships. Thus, the closed-form solution of the rotational motion parameters can be solved using the phase coefficients of the azimuth signal corresponding to the determined scattering point, thereby avoiding complex iterative calculations and improving the efficiency and accuracy of azimuth calibration of spaceborne radar images.

[0067] It should be understood that, in the embodiments of this application, the azimuth signal refers to the azimuth-dimensional signal received by the spaceborne radar and formed after range compression processing. The azimuth signal reflects the echo characteristics of the target in the azimuth direction. The rotational motion parameters determine the azimuth-oriented scale change caused by the target's rotational motion during imaging, and are the core parameters for achieving lateral calibration. By estimating the rotational motion parameters, the pixel size in the spaceborne radar image can be converted into the actual size in physical space, thereby completing the reconstruction of the target's shape and size.

[0068] For example, in another possible implementation, the first mapping relationship can be determined through the following steps 11 to 12:

[0069] Step 11: Establish a high-precision model of the space target's satellite-borne radar echo signal.

[0070] With translational motion compensation completed, the space target satellite radar imaging model can be equivalent to a turntable imaging model. Then, the slant range history of a scattering point P on the space target can be expressed as the following formula (1) (i.e., the fourth mapping relationship):

[0071] R p (t m ) = R p +y p cosθ(t m )+x p sinθ(t m (1)

[0072] The initial position of the scattering point P can be represented as [x p ,y p ] T x p and y p These represent the initial distance and orientation positions, respectively. [·] T Indicates transpose, R p t is the slant range between the radar and the target's rotation center. m Representing slow time, θ(t) m () represents the equivalent rotation angle.

[0073] The equivalent rotational motion between the spaceborne radar and the space target is modeled as uniformly accelerated rotational motion, with an equivalent rotation angle θ(t) m It can be expressed as the following formula (2):

[0074]

[0075] Where ω and α represent the equivalent initial rotational velocity and equivalent rotational acceleration, respectively.

[0076] According to formula (2), combined with the Maclaurin series, the slant distance history in formula (1) can be rewritten as formula (3):

[0077]

[0078] If the cross-range cell migration correction has been completed and the range has been compressed, the azimuth signal of the scattering point P can be expressed as the following formula (4) (i.e., the fifth mapping relationship):

[0079]

[0080] Among them, s a (t m ) represents the azimuth signal, exp{·} represents the exponential function, and j is the imaginary number. 2 =-1, f c denoted as carrier frequency, and c as the speed of light.

[0081] Based on the above formulas (3) and (4), we obtain the following formula (5) (i.e., the second mapping relationship):

[0082]

[0083] Formula (5) models the azimuth signal as a cubic phase function, which fully considers the modulation of the phase coefficients of the azimuth signal by each order based on the target rotation motion characteristics, and provides an accurate model basis for high-precision rotation motion parameter estimation and lateral calibration.

[0084] Step 12: Construct the mapping relationship between the phase parameter domain and the motion parameter domain.

[0085] The azimuth signal in formula (5) can be further expressed as formula (6) (i.e., an example of the third mapping relationship):

[0086]

[0087] Where, β p,i Let i represent the i-th phase coefficient of the azimuth signal, where i = 1, 2, 3.

[0088] Combining formulas (5) and (6), the mapping relationship between the phase parameter domain and the motion parameter domain is constructed as shown in formula (7) (i.e., an example of the first mapping relationship):

[0089]

[0090] According to formula (7), the phase coefficient β can be seen. p,i The high coupling relationship between the rotational motion parameters {ω,α} is essentially a system of multivariate nonlinear equations. By solving the system of equations, the closed solution of the equivalent rotational motion parameters can be obtained, providing theoretical support for high-precision estimation of rotational motion parameters and lateral calibration.

[0091] In step 103, the azimuth resolution of the spaceborne radar image is determined based on the rotational motion parameters of at least one scattering point.

[0092] It should be understood that, in the embodiments of this application, the azimuth resolution is not limited, and the azimuth resolution refers to the resolution of the spaceborne radar image in the azimuth direction. In some embodiments, the azimuth resolution of the spaceborne radar image refers to the minimum distance at which the radar can distinguish two adjacent scattering points in the direction of satellite motion. For example, in one possible implementation, if the azimuth resolution of the spaceborne radar image is 5 meters, it means that when the azimuth distance between two scattering points is less than 5 meters, the two scattering points will overlap into one point in the azimuth direction of the spaceborne radar image.

[0093] In this application embodiment, the specific implementation of determining the azimuth resolution of the spaceborne radar image based on the rotational motion parameters of at least one scattering point is not limited. In some embodiments, Figure 2 This application provides a schematic diagram of an implementation process for determining the azimuth resolution size, as shown in the embodiment. Figure 2 As shown, the azimuth resolution of the spaceborne radar image can be determined based on the rotational motion parameters of at least one scattering point through the following steps 201 to 203:

[0094] Step 201: Determine the average value of the initial rotational velocities of the multiple scattering points to obtain the average initial rotational velocity;

[0095] Step 202: Determine the average value of the rotational acceleration of the multiple scattering points to obtain the average rotational acceleration;

[0096] Step 203: Determine the azimuth resolution of the spaceborne radar image based on the average initial rotation velocity and the average rotation acceleration.

[0097] It is understood that in this embodiment, the azimuth resolution of the spaceborne radar image is not determined based on the rotational motion parameters of a single scattering point. Instead, the average of the initial rotational velocities and the average of the rotational accelerations of multiple scattering points are calculated. The azimuth resolution of the spaceborne radar image is then determined based on the average initial rotational velocity and the average rotational acceleration. This reduces the instability or noise caused by estimating rotational motion parameters using a single scattering point, and provides a more stable and reliable azimuth resolution estimate, thereby improving the overall accuracy of lateral calibration.

[0098] For example, in one possible implementation, the rotational motion parameters of multiple scattering points that satisfy the first condition are averaged by the following formula (8) to obtain a smoothed rotational motion parameter estimation result, thereby reducing the instability or noise impact caused by a single estimation.

[0099]

[0100] Where p represents the number of scattering points that satisfy the first condition. Indicates the average initial rotational velocity. Represents the average rotational acceleration. This represents the initial rotational velocity of the p-th scattering point. This represents the rotational acceleration of the p-th scattering point.

[0101] In some embodiments, determining the azimuth resolution of the spaceborne radar image based on the average initial rotation velocity and the average rotation acceleration further includes: determining the azimuth resolution of the spaceborne radar image based on the average initial rotation velocity, the average rotation acceleration, and the coherent accumulation time of the spaceborne radar image.

[0102] It is understood that, in the embodiments of this application, the coherent accumulation time of the spaceborne radar image affects the synthetic aperture length in the azimuth direction. Therefore, by jointly determining the resolution of the spaceborne radar image in the azimuth direction based on the average initial rotational velocity, average rotational acceleration, and coherent accumulation time of the spaceborne radar image, the actual resolution of the spaceborne radar image in the azimuth direction can be more accurate, thereby improving the azimuth calibration accuracy of the spaceborne radar image. This enhances the ability to reconstruct the true size and shape of space targets and is more suitable for the calibration of highly dynamic, non-cooperative space targets.

[0103] In this embodiment, the coherent accumulation time of the spaceborne radar image is not limited. The coherent accumulation time of the spaceborne radar image refers to the duration of the continuous signal used for coherent synthesis during radar signal processing. The coherent accumulation time of the spaceborne radar image directly affects its signal-to-noise ratio and resolution, especially in inverse synthetic aperture radar (ISAR) imaging, where the coherent accumulation time determines the azimuth synthetic aperture length. A longer coherent accumulation time can improve azimuth resolution, but it is also limited by the motion characteristics of space targets and Doppler bandwidth.

[0104] For example, in one possible implementation, a range-instantaneous Doppler (RID) algorithm is used to generate instantaneous satellite-borne radar images of space targets (i.e., an example of satellite-borne radar images). The range-instantaneous Doppler algorithm obtains a focused radar image by estimating the Doppler history, selecting the imaging time, and obtaining a specific Doppler frequency.

[0105] For imaging time t i The size of the azimuth resolution cell in the RID image (an example of a spaceborne radar image). (i.e., the horizontal scaling factor) can be calculated using the following formula (9):

[0106]

[0107] Among them, t i This indicates the selected imaging time, where T is the coherence accumulation time. The wavelength of the transmitted signal.

[0108] In step 104, the azimuth direction of the spaceborne radar image is calibrated according to the azimuth resolution to obtain the calibrated spaceborne radar image.

[0109] In some embodiments, the azimuth orientation of the spaceborne radar image can be calibrated according to the azimuth resolution as follows: by applying the calculated azimuth resolution to the scaling transformation of the azimuth coordinates of the radar image, the image is horizontally stretched or compressed to conform to the actual physical size of the target.

[0110] Furthermore, in some embodiments, the azimuth coordinates of the space target satellite radar instantaneous image generated by the range-instantaneous Doppler algorithm are redefined by combining the calculated lateral calibration factor, so that the actual length represented by each pixel is consistent with the true size of the target.

[0111] For example, in one possible implementation, if the solar panel spans 568 pixel units in the range dimension and 501 pixel units in the azimuth dimension of a space target in a spaceborne radar image, the solar panel occupies approximately 757 pixel units. By range compression, the range resolution is obtained, thus determining that the solar panel spans 6.7648 meters (m) in the range dimension. However, the azimuth resolution is unknown. Using the azimuth calibration method for spaceborne radar images provided in one or more of the above embodiments, the azimuth resolution of the solar panel is obtained, thus determining that the solar panel spans 20.9717 m in the azimuth dimension. Finally, the length of the solar panel is determined to be 22.0358 m.

[0112] The following examples illustrate possible implementation schemes for the azimuth calibration method for spaceborne radar images described in one or more of the above embodiments.

[0113] Lateral calibration (an example of azimuth calibration) is a key technology for reconstructing the true size and shape of a target. It enables precise calibration of radar image scale and is crucial for target feature extraction and recognition. In high-precision spaceborne radar imaging, the range dimension can be directly obtained through range compression, while the azimuth dimension is closely related to the target's equivalent rotational motion. Since imaging targets are typically non-cooperative, their prior motion information is difficult to obtain. Therefore, lateral calibration techniques are needed to estimate the equivalent rotational motion parameters and calibrate the target's azimuth dimensions. However, in spaceborne radar imaging of space targets, the high relative speed and rapid attitude changes between the radar and the target undoubtedly increase the difficulty of azimuth scale calibration, affecting the accurate reconstruction of the target's size and shape in the image and limiting the application effectiveness of spaceborne radar imaging technology in state perception and mission decision-making. Therefore, it is urgent to develop precise lateral calibration techniques to achieve accurate azimuth dimension calibration of space targets in spaceborne radar images, thereby enhancing the image's ability to interpret space targets and promoting the practical value of spaceborne radar imaging technology.

[0114] Therefore, to meet the practical need for fast and stable lateral calibration of space target spaceborne radar images, this application proposes an analytical method for lateral calibration of space target spaceborne radar images (i.e., an example of an azimuth calibration method for spaceborne radar images). This method achieves high-precision lateral calibration by directly solving the closed solution of the rotational motion parameters, avoiding the accumulation of estimation errors and eliminating the need for complex iterative processes. It features high estimation accuracy, low computational complexity, and stable lateral calibration results, making it suitable for high-dynamic spaceborne radar imaging scenarios.

[0115] For example, the analytical space target spaceborne radar image lateral calibration method provided in this application embodiment can be implemented through the following steps 21 to 26:

[0116] Step 21: Establish a high-precision model of the space target's satellite-borne radar echo signal.

[0117] With translational motion compensation completed, the space target satellite radar imaging model can be equivalent to a turntable imaging model. Then, the slant range history of a scattering point P on the space target can be expressed as the following formula (10) (i.e., the fourth mapping relationship):

[0118] R p (t m ) = R p +y p cosθ(t m )+x p sinθ(t m (10)

[0119] The initial position of the scattering point P can be represented as [x p ,y p ] T x p and y p These represent the initial distance and orientation positions, respectively. [·] T Indicates transpose, R p t is the slant range between the radar and the target's rotation center. m Representing slow time, θ(t) m () represents the equivalent rotation angle.

[0120] The equivalent rotational motion between the spaceborne radar and the space target is modeled as uniformly accelerated rotational motion, with an equivalent rotation angle θ(t) m It can be expressed as the following formula (11):

[0121]

[0122] Where ω and α represent the equivalent initial rotational velocity and equivalent rotational acceleration, respectively.

[0123] According to formula (11), combined with the Maclaurin series, the slant distance history in formula (10) can be rewritten as formula (12):

[0124]

[0125] If the cross-range cell migration correction has been completed and the range has been compressed, the azimuth signal of the scattering point P can be expressed as the following formula (13) (i.e., the fifth mapping relationship):

[0126]

[0127] Among them, s a (t m ) represents the azimuth signal, exp{·} represents the exponential function, and j is the imaginary number.2 =-1, f c denoted as carrier frequency, and c as the speed of light.

[0128] Based on the above formulas (12) and (13), we obtain the following formula (14) (i.e., the second mapping relationship):

[0129]

[0130] Formula (14) models the azimuth signal as a cubic phase function, which fully considers the modulation of the phase coefficients of the azimuth signal by each order based on the target rotation motion characteristics, and provides an accurate model basis for high-precision rotation motion parameter estimation and lateral calibration.

[0131] Step 22: Construct the mapping relationship between the phase parameter domain and the motion parameter domain.

[0132] The azimuth signal in formula (14) can be further expressed as formula (15) (i.e., an example of the third mapping relationship):

[0133]

[0134] Where, β p,i Let i represent the i-th phase coefficient of the azimuth signal, where i = 1, 2, 3.

[0135] Combining formulas (14) and (15), the mapping relationship between the phase parameter domain and the motion parameter domain is constructed as shown in formula (16) (i.e., an example of the first mapping relationship):

[0136]

[0137] According to formula (16), the phase coefficient β can be seen. p,i The high coupling relationship between the rotational motion parameters {ω,α} is essentially a system of multivariate nonlinear equations. By solving the system of equations, the closed solution of the equivalent rotational motion parameters can be obtained, providing theoretical support for high-precision estimation of rotational motion parameters and lateral calibration.

[0138] Step 23: Use the phase parameter estimation method to estimate the phase coefficients of each order of the azimuth signal.

[0139] Phase parameters are estimated for each order of phase coefficients in the above formula (16). The phase coefficients of each order of the scattering point can be obtained by phase parameter estimation methods. For example, the third-order phase coefficients of the azimuth signal can be estimated using the Product Generalized Cubic Phase Function (PGCPF). The Product Generalized Cubic Phase Function achieves signal energy aggregation through delay, correlation, and Fourier transform, thereby accurately estimating the third-order phase coefficients, and has advantages such as suppressing cross terms and improving noise immunity.

[0140] Based on the estimated third-order phase coefficients, the cubic phase is demodulated, and the remaining azimuth signal can be considered as a linear frequency modulated signal. Then, the second-order phase coefficients of the azimuth signal are estimated using the integrated cubic phase function (ICPF). The kernel function of the ICPF can concentrate the signal energy at the second-order phase coefficients, thereby achieving accurate estimation of the second-order phase coefficients and effectively suppressing cross-terms, making it suitable for low signal-to-noise ratio scenarios.

[0141] Based on the estimated second-order phase coefficients, the second-order phase is demodulated, and the remaining azimuth signal can be regarded as a single-frequency signal. Then, the first-order phase coefficients of the azimuth signal are estimated using the delinear frequency modulation (Decirp) method, which has the advantages of low computational complexity and simple implementation.

[0142] Let the estimated phase parameter of the scattering point P be β. p,i (i = 1, 2, 3). For cases where there are multiple scattering points on a single range cell, the CLEAN technique is used to eliminate scattering points with estimated phase coefficients of each order.

[0143] Step 24: Find the scattering point that satisfies the condition of a unique real solution.

[0144] When the phase coefficient of the scattering point P satisfies the following condition, the unique real solution of the rotational motion parameters can be obtained according to the following formula (17):

[0145] β p,1 ·β p,3 <0 (17)

[0146] The phase coefficients of scattering points that satisfy the conditions shown in formula (17) (i.e., an example of the first condition) are retained for subsequent analytical estimation of rotational motion parameters.

[0147] Step 25: Combine the phase coefficient estimation results to achieve analytical estimation of rotational motion parameters.

[0148] Based on formula (17), and combined with the phase coefficients of the scattering point P estimated in step 23, the unique real solution of the rotational motion parameters is obtained using the following formula (18):

[0149]

[0150] in, and The rotational motion parameters obtained by solving using the estimated phase coefficient of the scattering point P, where A, B, C, ρ and ξ are intermediate variables, are expressed by the following formula (19):

[0151]

[0152] The rotational motion parameters of multiple scattering points that meet the first condition are averaged using the following formula (20) to obtain a smoothed estimation result of the rotational motion parameters, thereby reducing the instability or noise impact caused by a single estimation.

[0153]

[0154] Where p represents the number of scattering points that satisfy formula (17), Indicates the average initial rotational velocity. Represents the average rotational acceleration. This represents the initial rotational velocity of the p-th scattering point. This represents the rotational acceleration of the p-th scattering point.

[0155] Step 26: Generate instantaneous images of space target satellite radar using the range-instantaneous Doppler algorithm, calculate the lateral calibration factor, and calibrate the instantaneous images of space target satellite radar.

[0156] The Range-Instantaneous Doppler (RID) algorithm is used to generate instantaneous satellite-borne radar images of space targets (i.e., an example of satellite-borne radar images). The RID algorithm obtains a focused radar image by estimating the Doppler history, selecting the imaging time, and thus obtaining a specific Doppler frequency.

[0157] For imaging time t i The size of the azimuth resolution cell in the RID image (an example of a spaceborne radar image). (That is, the horizontal scaling factor, which is also an example of resolution size) can be calculated by the following formula (21):

[0158]

[0159] Among them, t i This indicates the selected imaging time, where T is the coherence accumulation time. The wavelength of the transmitted signal.

[0160] Using orientation to distinguish unit size By defining the scale (i.e., lateral calibration) of the azimuth coordinates of the RID image, a physically calibrated spaceborne radar image can be obtained.

[0161] For example, in one possible implementation, simulation imaging processing is performed on the orbital parameters of the spaceborne radar and the space target shown in Table 1 and the radar simulation parameters shown in Table 2, and calibration results are obtained to verify the effectiveness of the azimuth calibration method for spaceborne radar images provided in the embodiments of this application.

[0162] Table 1. Orbital parameters of spaceborne radar and space targets

[0163]

[0164] Table 2 Simulation Parameters of Spaceborne Radar

[0165]

[0166] Figure 3 A spatial target scattering point model provided in this application embodiment, in Figure 3 In the middle, the solar panel span is 20.9416m.

[0167] Figure 4 This application provides an example of a space-based radar image of a target without azimuth calibration, such as... Figure 4 As shown, due to the unknown size of the orientation unit, the two-dimensional scale of the image is severely distorted, making it impossible to know the true shape and size of the spatial target.

[0168] Using the azimuth calibration method for spaceborne radar images provided in the embodiments of this application, Figure 4 The space target spaceborne radar image shown below, which has not undergone lateral calibration, is calibrated. The calibrated space target spaceborne radar image is as follows: Figure 5 As shown. In Figure 5 In the middle, the target two-dimensional scale and Figure 3 The scattering point model shown has a consistent two-dimensional scale.

[0169] Table 3 compares the true and estimated values ​​of equivalent rotational velocity, equivalent rotational acceleration, and solar panel span. The relative errors of the estimated equivalent rotational velocity and equivalent rotational acceleration are only 6.9656% and 5.2619%, respectively, indicating high estimation accuracy that meets the requirements for high-precision lateral calibration. The solar panel span of the space target, calculated from radar images, is 22.0358 m, with a relative error of only 5.2250% compared to the true value, achieving high-precision estimation of the space target's size.

[0170] Table 3 Comparison of estimated values ​​and true values

[0171]

[0172] It should be noted that although the steps of the method in this application are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps; or steps from different embodiments may be combined into a new technical solution.

[0173] Based on the foregoing embodiments, this application provides an image processing device, which includes the included modules and the units included in each module, which can be implemented by a processor; of course, it can also be implemented by specific logic circuits; in the implementation process, the processor can be an AI acceleration engine (such as NPU), GPU, central processing unit (CPU), microprocessor (MPU), digital signal processor (DSP) or field programmable gate array (FPGA), etc.

[0174] Figure 6 This is a schematic diagram of the azimuth calibration device for spaceborne radar images provided in the embodiments of this application, as shown below. Figure 6 As shown, the azimuth calibration device 600 for spaceborne radar images includes a first determining module 601, a second determining module 602, a third determining module 603, and a calibration module 604, wherein:

[0175] The first determining module 601 is configured to determine the phase coefficients of each order of the azimuth signal corresponding to the scattering point in the spaceborne radar image.

[0176] The second determining module 602 is configured to determine the rotational motion parameters of each scattering point based on the phase coefficients of each order and the first mapping relationship; the rotational motion parameters include: initial rotational velocity and rotational acceleration; the first mapping relationship is used to characterize the mapping relationship between the phase coefficients of each order and the rotational motion parameters respectively;

[0177] The third determining module 603 is configured to determine the azimuth resolution of the spaceborne radar image based on the rotational motion parameters of at least one scattering point.

[0178] The calibration module 604 is configured to calibrate the azimuth direction of the spaceborne radar image according to the azimuth resolution size, so as to obtain the calibrated spaceborne radar image.

[0179] In some embodiments, the phase coefficients include: a first-order phase coefficient, a second-order phase coefficient, and a third-order phase coefficient; the second determining module 602 is configured to determine the rotational motion parameters of the scattering point based on the phase coefficients and the first mapping relationship when the relationship between the first-order phase coefficient and the third-order phase coefficient satisfies a first condition; wherein, in the first mapping relationship, the relationship between the phase coefficients and the initial rotational velocity and the rotational acceleration is an Nth-order nonlinear relationship; N is the order corresponding to the phase coefficients; the first condition includes: the first-order phase coefficient is greater than 0 and the third-order phase coefficient is less than 0; or, the first-order phase coefficient is less than 0 and the third-order phase coefficient is greater than 0; or, the product between the first-order phase coefficient and the third-order phase coefficient is less than 0.

[0180] In some embodiments, the second determining module 602 is configured to obtain candidate rotational motion parameters of the scattering point based on the phase coefficients of each order and the first mapping relationship; and to determine the candidate rotational motion parameters that satisfy the second condition as the rotational motion parameters of the scattering point; wherein the second condition is that the numerical value corresponding to the candidate rotational motion parameter is a real number.

[0181] In some embodiments, the third determining module 603 is configured to determine the average value of the initial rotational velocities of the plurality of scattering points to obtain an average initial rotational velocity; determine the average value of the rotational accelerations of the plurality of scattering points to obtain an average rotational acceleration; and determine the azimuth resolution of the spaceborne radar image based on the average initial rotational velocity and the average rotational acceleration.

[0182] In some embodiments, the third determining module 603 is configured to determine the azimuth resolution of the spaceborne radar image based on the average initial rotational velocity, the average rotational acceleration, and the coherent accumulation time of the spaceborne radar image.

[0183] In some embodiments, the first mapping relationship is obtained based on the second mapping relationship and the third mapping relationship; wherein, the second mapping relationship is used to characterize the mapping relationship between the azimuth signal corresponding to the scattering point in the spaceborne radar image and the rotational motion parameter; the third mapping relationship is used to characterize the mapping relationship between the azimuth signal corresponding to the scattering point and the phase coefficients of each order of the azimuth signal.

[0184] In some embodiments, the first determining module 601 is configured to determine the phase coefficients of the azimuth signal corresponding to the m-th scattering point in the spaceborne radar image; clear the m-th scattering point in the spaceborne radar image, and perform the next step of determining the phase coefficients of the azimuth signal corresponding to the scattering point in the spaceborne radar image, until the energy of the azimuth signal corresponding to the remaining scattering point is less than or equal to the energy threshold.

[0185] The descriptions of the above device embodiments are similar to those of the above method embodiments, and have similar beneficial effects. For technical details not disclosed in the device embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0186] It should be noted that the module division in the embodiments of this application is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, exist as separate physical units, or have two or more units integrated into one unit. The integrated units can be implemented in hardware, as software functional units, or a combination of software and hardware.

[0187] It should be noted that, in the embodiments of this application, if the above-described methods are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to related technologies, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware and software combination.

[0188] This application provides an electronic device. Figure 7 Schematic diagram of the structure of the electronic device provided in the embodiments of this application Figure Two ,like Figure 7 As shown, the electronic device 70 includes a memory 701 and a processor 702. The memory 701 stores a computer program that can run on the processor 702. When the processor 702 executes the program, it implements the steps in the method provided in the above embodiments.

[0189] It should be noted that the memory 701 is configured to store instructions and applications executable by the processor 702, and can also cache data to be processed or already processed (e.g., image data, audio data, voice communication data and video communication data) in the processor 702 and various modules in the electronic device 70. It can be implemented by flash memory or random access memory (RAM).

[0190] This application also provides a computer-readable storage medium for storing computer programs.

[0191] Optionally, the computer-readable storage medium can be applied to the electronic device in the embodiments of this application, and the computer program causes the processor to execute the various methods of the embodiments of this application, which will not be described in detail here for the sake of brevity.

[0192] This application also provides a computer program product, including computer program instructions.

[0193] Optionally, the computer program product can be applied to the electronic device in the embodiments of this application, and the computer program instructions cause the processor to execute the various methods in the embodiments of this application, which will not be described in detail here for the sake of brevity.

[0194] This application also provides a computer program.

[0195] Optionally, the computer program can be applied to the electronic device in the embodiments of this application. When the computer program runs on the processor, it causes the processor to execute the various methods of the embodiments of this application. For the sake of brevity, these will not be described in detail here.

[0196] It should be noted that the descriptions of the electronic devices, storage media, computer program products, and computer program embodiments above are similar to the descriptions of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the electronic devices, storage media, computer program products, and computer program embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0197] It should be understood that the phrases "one embodiment," "an embodiment," or "some embodiments" mentioned throughout the specification mean that a specific feature, structure, or characteristic related to an embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment," "in one embodiment," or "in some embodiments" appearing throughout the specification do not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely for descriptive purposes and do not represent the superiority or inferiority of the embodiments. The descriptions of the various embodiments above tend to emphasize the differences between the various embodiments; their similarities or commonalities can be referred to mutually, and for the sake of brevity, they will not be repeated here.

[0198] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three kinds of relationships. For example, object A and / or object B can represent three situations: object A exists alone, object A and object B exist simultaneously, and object B exists alone.

[0199] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0200] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple modules or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or modules can be electrical, mechanical, or other forms.

[0201] The modules described above as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules. They may be located in one place or distributed across multiple network units. Some or all of the modules may be selected to achieve the purpose of this embodiment according to actual needs.

[0202] In addition, each functional module in the various embodiments of this application can be integrated into one processing unit, or each module can be a separate unit, or two or more modules can be integrated into one unit; the integrated modules can be implemented in hardware or in the form of hardware plus software functional units.

[0203] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0204] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to related technologies, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0205] The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0206] The features disclosed in the several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0207] The features disclosed in the several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method or device embodiments.

[0208] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for azimuth calibration of spaceborne radar images, characterized in that, The method includes: Determine the phase coefficients of each order of the azimuth signal corresponding to the scattering point in the spaceborne radar image; For each scattering point, the rotational motion parameters of the scattering point are determined according to the phase coefficients of each order and the first mapping relationship; the rotational motion parameters include: initial rotational velocity and rotational acceleration; the first mapping relationship is used to characterize the mapping relationship between the phase coefficients of each order and the rotational motion parameters respectively; The azimuth resolution of the spaceborne radar image is determined based on the rotational motion parameters of at least one scattering point. Based on the azimuth resolution, the azimuth direction of the spaceborne radar image is calibrated to obtain the calibrated spaceborne radar image.

2. The method according to claim 1, characterized in that, The phase coefficients of each order include: first-order phase coefficient, second-order phase coefficient, and third-order phase coefficient; determining the rotational motion parameters of the scattering point based on the phase coefficients of each order and the first mapping relationship includes: When the relationship between the first-order phase coefficient and the third-order phase coefficient satisfies the first condition, the rotational motion parameters of the scattering point are determined according to the phase coefficients and the first mapping relationship; wherein, in the first mapping relationship, the relationship between the phase coefficients and the initial rotational velocity and the rotational acceleration is an Nth-order nonlinear relationship; N is the order corresponding to the phase coefficients. The first condition includes: the first-order phase coefficient is greater than 0 and the third-order phase coefficient is less than 0; or, the first-order phase coefficient is less than 0 and the third-order phase coefficient is greater than 0; or, the product between the first-order phase coefficient and the third-order phase coefficient is less than 0.

3. The method according to claim 2, characterized in that, The step of determining the rotational motion parameters of the scattering point based on the phase coefficients of each order and the first mapping relationship includes: Based on the phase coefficients of each order and the first mapping relationship, the candidate rotational motion parameters of the scattering point are obtained; The candidate rotational motion parameters that satisfy the second condition are determined as the rotational motion parameters of the scattering point; the second condition is that the numerical value corresponding to the candidate rotational motion parameter is a real number.

4. The method according to any one of claims 1 to 3, characterized in that, Determining the azimuth resolution of the spaceborne radar image based on the rotational motion parameters of at least one scattering point includes: The average initial rotational velocity of the multiple scattering points is determined to obtain the average initial rotational velocity. The average rotational acceleration is obtained by determining the average rotational acceleration of the multiple scattering points. The azimuth resolution of the spaceborne radar image is determined based on the average initial rotation velocity and the average rotation acceleration.

5. The method according to claim 4, characterized in that, The step of determining the azimuth resolution of the spaceborne radar image based on the average initial rotation velocity and the average rotation acceleration further includes: The azimuth resolution of the spaceborne radar image is determined based on the average initial rotational velocity, the average rotational acceleration, and the coherent accumulation time of the spaceborne radar image.

6. The method according to any one of claims 1 to 3, characterized in that, The first mapping relationship is obtained based on the second mapping relationship and the third mapping relationship; wherein, the second mapping relationship is used to characterize the mapping relationship between the azimuth signal corresponding to the scattering point in the spaceborne radar image and the rotational motion parameter; the third mapping relationship is used to characterize the mapping relationship between the azimuth signal corresponding to the scattering point and the phase coefficients of each order of the azimuth signal.

7. The method according to any one of claims 1 to 3, characterized in that, The determination of the phase coefficients of each order of the azimuth signal corresponding to the scattering point in the spaceborne radar image includes: Determine the phase coefficients of each order of the azimuth signal corresponding to the m-th scattering point in the spaceborne radar image; The m-th scattering point in the spaceborne radar image is cleared, and the next step of determining the phase coefficients of each order of the azimuth signal corresponding to the scattering point in the spaceborne radar image is performed until the energy of the azimuth signal corresponding to the remaining scattering point is less than or equal to the energy threshold.

8. A azimuth calibration device for spaceborne radar images, characterized in that, The device includes: The first determining module is configured to determine the phase coefficients of each order of the azimuth signal corresponding to the scattering point in the spaceborne radar image; The second determining module is configured to determine the rotational motion parameters of each scattering point based on the phase coefficients of each order and the first mapping relationship; the rotational motion parameters include: initial rotational velocity and rotational acceleration; the first mapping relationship is used to characterize the mapping relationship between the phase coefficients of each order and the rotational motion parameters respectively; The third determining module is configured to determine the azimuth resolution of the spaceborne radar image based on the rotational motion parameters of at least one scattering point. The calibration module is configured to calibrate the azimuth direction of the spaceborne radar image according to the azimuth resolution, so as to obtain the calibrated spaceborne radar image.

9. An electronic device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the program, it implements the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the method described in any one of claims 1 to 7.

11. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the method described in any one of claims 1 to 7.

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